Trends In Sea Ice Extent Research Articles

Automated parameter tuning applied to sea ice in a global climate model

This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.

Increase of the Antarctic Sea Ice Extent is highly significant only in the Ross Sea

In the context of global warming, the question of why Antarctic sea ice extent (SIE) has increased is one of the most fundamental unsolved mysteries. Although many mechanisms have been proposed, it is still unclear whether the increasing trend is anthropogenically originated or only caused by internal natural variability. In this study, we employ a new method where the underlying natural persistence in the Antarctic SIE can be correctly accounted for. We find that the Antarctic SIE is not simply short-term persistent as assumed in the standard significance analysis, but actually characterized by a combination of both short- and long-term persistence. By generating surrogate data with the same persistence properties, the SIE trends over Antarctica (as well as five sub-regions) are evaluated using Monte-Carlo simulations. It is found that the SIE trends over most sub-regions of Antarctica are not statistically significant. Only the SIE over Ross Sea has experienced a highly significant increasing trend (p = 0.008) which cannot be explained by natural variability. Influenced by the positive SIE trend over Ross Sea, the SIE over the entire Antarctica also increased over the past decades, but the trend is only at the edge of being significant (p = 0.034).

Sensitivity of Antarctic sea ice to the Southern Annular Mode in coupled climate models

We assess the sea ice response to Southern Annular Mode (SAM) anomalies for pre-industrial control simulations from the Coupled Model Intercomparison Project (CMIP5). Consistent with work by Ferreira et al. (J Clim 28:1206–1226, 2015. doi:10.1175/JCLI-D-14-00313.1), the models generally simulate a two-timescale response to positive SAM anomalies, with an initial increase in ice followed by an eventual sea ice decline. However, the models differ in the cross-over time at which the change in ice response occurs, in the overall magnitude of the response, and in the spatial distribution of the response. Late twentieth century Antarctic sea ice trends in CMIP5 simulations are related in part to different modeled responses to SAM variability acting on different time-varying transient SAM conditions. This explains a significant fraction of the spread in simulated late twentieth century southern hemisphere sea ice extent trends across the model simulations. Applying the modeled sea ice response to SAM variability but driven by the observed record of SAM suggests that variations in the austral summer SAM, which has exhibited a significant positive trend, have driven a modest sea ice decrease. However, additional work is needed to narrow the considerable model uncertainty in the climate response to SAM variability and its implications for 20th–21st century trends.

Circumpolar vegetation dynamics product for global change study

Abstract Land surface phenology (LSP) and vegetation growth of the circumpolar north are changing in response to more pronounced warming in the region. We here introduce the first phenology index (PI) based vegetation dynamics product, comprising start (SOS), end (EOS), length of growing season (LOS), and growing season integrated annual normalized difference vegetation index (NDVI), specifically designed for the entire circumpolar north (> 45°N) using SPOT VGT data starting from 1999. PI combines the merits of NDVI and normalized difference infrared index (NDII) by taking the difference of squared greenness (from NDVI) and wetness (from NDII) to remove the soil and snow cover dynamics from key vegetation LSP cycles. The results show that the circumpolar vegetation dynamics and their spatial distributions are realistically detected. Further validation based on North American and European deciduous broadleaf, evergreen needleleaf and mixed forests, and wetland flux tower sites shows good agreements between the LSP dates from the circumpolar vegetation dynamics and ground phenology estimates from CO 2 flux measurements. The validation also proves that the circumpolar vegetation dynamics product is an improvement over the operational global MODIS Combined Land Cover Dynamics (MCD12Q2) product for the circumpolar region. The results are further compared with the interannual variability of sea ice extent and leading teleconnection patterns in the region. The circumpolar averaged results show that, the growing season integrated annual NDVI is significantly increasing (0.68% year − 1 , p = 0.006) and well correlated with the growing season sea ice extent trend ( p = 0.007). The circumpolar vegetation dynamics is more related to Polar/Eurasia pattern (i.e., indicator of circumpolar vortex) than to Scandinavian Pattern (SCA) and North Atlantic Oscillation (NAO). In view of the considerable scientific and policy importance of the circumpolar region, particularly the arctic ecosystems, the presented circumpolar vegetation dynamics product will greatly contribute to study changes in plant growth, phenology, photosynthetic capacity, and associated feedbacks under climate change.

Circumpolar habitat use in the southern elephant seal: implications for foraging success and population trajectories

AbstractIn the Southern Ocean, wide‐ranging predators offer the opportunity to quantify how animals respond to differences in the environment because their behavior and population trends are an integrated signal of prevailing conditions within multiple marine habitats. Southern elephant seals in particular, can provide useful insights due to their circumpolar distribution, their long and distant migrations and their performance of extended bouts of deep diving. Furthermore, across their range, elephant seal populations have very different population trends. In this study, we present a data set from the International Polar Year project; Marine Mammals Exploring the Oceans Pole to Pole for southern elephant seals, in which a large number of instruments (N = 287) deployed on animals, encompassing a broad circum‐Antarctic geographic extent, collected in situ ocean data and at‐sea foraging metrics that explicitly link foraging behavior and habitat structure in time and space. Broadly speaking, the seals foraged in two habitats, the relatively shallow waters of the Antarctic continental shelf and the Kerguelen Plateau and deep open water regions. Animals of both sexes were more likely to exhibit area‐restricted search (ARS) behavior rather than transit in shelf habitats. While Antarctic shelf waters can be regarded as prime habitat for both sexes, female seals tend to move northwards with the advance of sea ice in the late autumn or early winter. The water masses used by the seals also influenced their behavioral mode, with female ARS behavior being most likely in modified Circumpolar Deepwater or northerly Modified Shelf Water, both of which tend to be associated with the outer reaches of the Antarctic Continental Shelf. The combined effects of (1) the differing habitat quality, (2) differing responses to encroaching ice as the winter progresses among colonies, (3) differing distances between breeding and haul‐out sites and high quality habitats, and (4) differing long‐term regional trends in sea ice extent can explain the differing population trends observed among elephant seal colonies.

Quantifying the contribution of natural variability to September Arctic sea ice decline

Arctic sea ice extent has been declining in recent decades. There is ongoing debate on the contribution of natural internal variability to recent and future Arctic sea ice changes. In this study, we contrast the trends in the forced and unforced simulations of carefully selected global climate models with the extended observed Arctic sea ice records. The results suggest that the natural variability explains no more than 42.3% of the observed September sea ice extent trend during 35 a (1979–2013) satellite observations, which is comparable to the results of the observed sea ice record extended back to 1953 (61 a, less than 48.5% natural variability). This reinforces the evidence that anthropogenic forcing plays a substantial role in the observed decline of September Arctic sea ice in recent decades. The magnitude of both positive and negative trends induced by the natural variability in the unforced simulations is slightly enlarged in the context of increasing greenhouse gases in the 21st century. However, the ratio between the realizations of positive and negative trends change has remained steady, which enforces the standpoint that external forcing will remain the principal determiner of the decreasing Arctic sea ice extent trend in the future.

Recent changes in Antarctic Sea Ice.

In contrast to the Arctic, total sea ice extent (SIE) across the Southern Ocean has increased since the late 1970s, with the annual mean increasing at a rate of 186×10(3) km(2) per decade (1.5% per decade; p<0.01) for 1979-2013. However, this overall increase masks larger regional variations, most notably an increase (decrease) over the Ross (Amundsen-Bellingshausen) Sea. Sea ice variability results from changes in atmospheric and oceanic conditions, although the former is thought to be more significant, since there is a high correlation between anomalies in the ice concentration and the near-surface wind field. The Southern Ocean SIE trend is dominated by the increase in the Ross Sea sector, where the SIE is significantly correlated with the depth of the Amundsen Sea Low (ASL), which has deepened since 1979. The depth of the ASL is influenced by a number of external factors, including tropical sea surface temperatures, but the low also has a large locally driven intrinsic variability, suggesting that SIE in these areas is especially variable. Many of the current generation of coupled climate models have difficulty in simulating sea ice. However, output from the better-performing IPCC CMIP5 models suggests that the recent increase in Antarctic SIE may be within the bounds of intrinsic/internal variability.

Antarctic sea ice increase consistent with intrinsic variability of the Amundsen Sea Low

We investigate the relationship between atmospheric circulation variability and the recent trends in Antarctic sea ice extent (SIE) using Coupled Model Intercomparison Project Phase 5 (CMIP5) atmospheric data, ECMWF Interim reanalysis fields and passive microwave satellite data processed with the Bootstrap version 2 algorithm. Over 1979–2013 the annual mean total Antarctic SIE increased at a rate of 195 × 103 km2 dec−1 (1.6 % dec−1), p < 0.01. The largest regional positive trend of annual mean SIE of 119 × 103 km2 dec−1 (4.0 % dec−1) has been in the Ross Sea sector. Off West Antarctica there is a high correlation between trends in SIE and trends in the near-surface winds. The Ross Sea SIE seasonal trends are positive throughout the year, but largest in spring. The stronger meridional flow over the Ross Sea has been driven by a deepening of the Amundsen Sea Low (ASL). Pre-industrial control and historical simulations from CMIP5 indicate that the observed deepening of the ASL and stronger southerly flow over the Ross Sea are within the bounds of modeled intrinsic variability. The spring trend would need to continue for another 11 years for it to fall outside the 2 standard deviation range seen in 90 % of the simulations.

Trends in Polar Sea Ice Extent 1979-2015

A survey of trends in dispersed and concentrated sea ice extent in the Arctic in the northern summer and northern winter and in the Antarctic in the southern summer and southern winter for the period 1979-2015 shows a negative trend in dispersed and concentrated sea ice extent in the Arctic in the northern summer amid rising surface temperature in the northern hemisphere. The trend in concentrated sea ice extent in the Arctic summer is not uniform across the study period but mostly a phenomenon of the latter half from 1998-2014. A positive trend for dispersed sea ice extent in the Antarctic in winter amid rising winter temperature in the southern hemisphere is not matched by trends in concentrated sea ice extent and the degree of dispersion and is discounted as spurious. In the southern summer, we found no trends in sea ice extent in the Antarctic and no trend in mean surface temperature in the southern hemisphere. This work concerns only sea ice extent without considerations of the age, thickness, and total volume of sea ice.

Influence of freshwater input on the skill of decadal forecast of sea ice in the Southern Ocean

Abstract. Recent studies have investigated the potential link between the freshwater input derived from the melting of the Antarctic ice sheet and the observed recent increase in sea ice extent in the Southern Ocean. In this study, we assess the impact of an additional freshwater flux on the trend in sea ice extent and concentration in simulations with data assimilation, spanning the period 1850–2009, as well as in retrospective forecasts (hindcasts) initialised in 1980. In the simulations with data assimilation, the inclusion of an additional freshwater flux that follows an autoregressive process improves the reconstruction of the trend in ice extent and concentration between 1980 and 2009. This is linked to a better efficiency of the data assimilation procedure but can also be due to a better representation of the freshwater cycle in the Southern Ocean. The results of the hindcast simulations show that an adequate initial state, reconstructed thanks to the data assimilation procedure including an additional freshwater flux, can lead to an increase in the sea ice extent spanning several decades that is in agreement with satellite observations. In our hindcast simulations, an increase in sea ice extent is obtained even in the absence of any major change in the freshwater input over the last decades. Therefore, while the additional freshwater flux appears to play a key role in the reconstruction of the evolution of the sea ice in the simulation with data assimilation, it does not seem to be required in the hindcast simulations. The present work thus provides encouraging results for sea ice predictions in the Southern Ocean, as in our simulation the positive trend in ice extent over the last 30 years is largely determined by the state of the system in the late 1970s.

Comparing and contrasting the behaviour of Arctic and Antarctic sea ice over the 35 year period 1979-2013

AbstractWe examine the evolution of sea-ice extent (SIE) over both polar regions for 35 years from November 1978 to December 2013, as well as for the global total ice (Arctic plus Antarctic). Our examination confirms the ongoing loss of Arctic sea ice, and we find significant (p˂ 0.001) negative trends in all months, seasons and in the annual mean. The greatest rate of decrease occurs in September, and corresponds to a loss of 3 x 106 km2 over 35 years. The Antarctic shows positive trends in all seasons and for the annual mean (p˂0.01), with summer attaining a reduced significance (p˂0.10). Based on our longer record (which includes the remarkable year 2013) the positive Antarctic ice trends can no longer be considered ‘small’, and the positive trend in the annual mean of (15.29 ± 3.85) x 103 km2 a–1 is almost one-third of the magnitude of the Arctic annual mean decrease. The global annual mean SIE series exhibits a trend of (–35.29 ± 5.75) x 103 km2 a-1 (p&lt;0.01). Finally we offer some thoughts as to why the SIE trends in the Coupled Model Intercomparison Phase 5 (CMIP5) simulations differ from the observed Antarctic increases.

Impact of the initialisation on the predictability of the Southern Ocean sea ice at interannual to multi-decadal timescales

In this study, we assess systematically the impact of different initialisation procedures on the predictability of the sea ice in the Southern Ocean. These initialisation strategies are based on three data assimilation methods: the nudging, the particle filter with sequential importance resampling and the nudging proposal particle filter. An Earth system model of intermediate complexity is used to perform hindcast simulations in a perfect model approach. The predictability of the Antarctic sea ice at interannual to multi-decadal timescales is estimated through two aspects: the spread of the hindcast ensemble, indicating the uncertainty of the ensemble, and the correlation between the ensemble mean and the pseudo-observations, used to assess the accuracy of the prediction. Our results show that at decadal timescales more sophisticated data assimilation methods as well as denser pseudo-observations used to initialise the hindcasts decrease the spread of the ensemble. However, our experiments did not clearly demonstrate that one of the initialisation methods systematically provides with a more accurate prediction of the sea ice in the Southern Ocean than the others. Overall, the predictability at interannual timescales is limited to 3 years ahead at most. At multi-decadal timescales, the trends in sea ice extent computed over the time period just after the initialisation are clearly better correlated between the hindcasts and the pseudo-observations if the initialisation takes into account the pseudo-observations. The correlation reaches values larger than 0.5 in winter. This high correlation has likely its origin in the slow evolution of the ocean ensured by its strong thermal inertia, showing the importance of the quality of the initialisation below the sea ice.

A Decade of QuikSCAT Scatterometer Sea Ice Extent Data

Polar sea ice is an important input to global climate models and is considered to be a sensitive indicator of climate change. While originally designed only for wind estimation, radar backscatter measurements collected by wind scatterometers have proven useful for estimating the extent of sea ice. During the Quick Scatterometer (QuikSCAT) mission, SeaWinds data were used to operationally map the sea ice extent. The resulting sea ice maps were used to mask near-surface winds to support SeaWinds' primary mission of measuring near-surface winds over the ocean. This paper describes the operational SeaWinds sea ice extent mapping algorithm, provides validation comparisons, and presents results from the ten-year data product. Starting with enhanced resolution horizontal polarization and vertical polarization backscatter images, the algorithm employs an iterative maximum-likelihood classifier with fixed thresholds to segment sea ice and open ocean pixels. Residual classification errors are reduced through binary image processing techniques and sea ice growth/retreat constraint methods. The algorithm results are compared with sea ice concentrations derived from Special Sensor Microwave/Imager data and with RADARSAT synthetic aperture radar imagery. The results suggest differences in the sensitivities of active and passive products given their channel sets and specific algorithms. Derived sea ice extents over the full decade-long QuikSCAT mission data set are analyzed to show important trends in sea ice extent for the Antarctic and Arctic regions.

The MODIS ice surface temperature product as an indicator of sea ice minimum over the Arctic Ocean

This study examines the relationship between sea ice extent and ice surface temperature (IST) between 2000 and 2013 using daily IST products from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The empirical prediction of September sea ice extent using its trend and two climate variables—IST and wind vorticity—exhibits a statistically significant relationship (R=0.97) with a time lag, where IST maximum in summer (June–July) corresponds to the sea ice extent minimum in September. This suggests that IST may serve as an indicator of the basin-wide heat energy accumulated in the Arctic by solar radiation and large-scale atmospheric heat transport from lower latitudes. The process of inducing higher IST is related to the change of atmospheric circulation over the Arctic. Averaged IST and 850hPa relative vorticity of the polar region show a significant negative correlation (−0.57) in boreal summer (June–August), suggesting a weakening of the polar vortex in the case of warmer-than-normal IST conditions. Weakening of the polar vortex is accompanied by above-normal surface pressure. Minimum sea ice extent in September was successfully predicted by both multiple linear regression and machine learning support vector regression using preceding summer IST and wind vorticity along with the trend of sea ice extent (R2~0.95, cross validation RMSE of 3–4×105km2, and relative cross validation RMSE of 5–8%).

Decadal trends in the Antarctic sea ice extent ultimately controlled by ice–ocean feedback

Abstract. The large natural variability of the Antarctic sea ice is a key characteristic of the system that might be responsible for the small positive trend in sea ice extent observed since 1979. In order to gain insight of the processes responsible for this variability, we have analysed in a control simulation performed with a coupled climate model a positive ice–ocean feedback that amplifies sea ice variations. When sea ice concentration increases in a region, in particular close to the ice edge, the mixed layer depth tends to decrease. This can be caused by a net inflow of ice, and thus of freshwater, that stabilizes the water column. A second stabilizing mechanism at interannual timescales is associated with the downward salt transport due to the seasonal cycle of ice formation: brine is released in winter and mixed over a deep layer while the freshwater flux caused by ice melting is included in a shallow layer, resulting in a net vertical transport of salt. Because of this stronger stratification due to the presence of sea ice, more heat is stored at depth in the ocean and the vertical oceanic heat flux is reduced, which contributes to maintaining a higher ice extent. This positive feedback is not associated with a particular spatial pattern. Consequently, the spatial distribution of the trend in ice concentration is largely imposed by the wind changes that can provide the initial perturbation. A positive freshwater flux could alternatively be the initial trigger but the amplitude of the final response of the sea ice extent is finally set up by the amplification related to the ice–ocean feedback. Initial conditions also have an influence as the chance to have a large increase in ice extent is higher if starting from a state characterized by a low value.

Sea-ice extent and its trend provide limited metrics of model performance

Abstract. We examine how the evaluation of modelled sea-ice coverage against reality is affected by uncertainties in the retrieval of sea-ice coverage from satellite, by the usage of sea-ice extent to overcome these uncertainties, and by internal variability. We find that for Arctic summer sea ice, model biases in sea-ice extent can be qualitatively different from biases in sea-ice area. This is because about half of the CMIP5 models and satellite retrievals based on the Bootstrap and the ASI algorithm show a compact ice cover in summer with large areas of high-concentration sea ice, while the other half of the CMIP5 models and satellite retrievals based on the NASA Team algorithm show a loose ice cover. For the Arctic winter sea-ice cover, differences in grid geometry can cause synthetic biases in sea-ice extent that are larger than the observational uncertainty. Comparing the uncertainty arising directly from the satellite retrievals with those that arise from internal variability, we find that the latter by far dominates the uncertainty estimate for trends in sea-ice extent and area: most of the differences between modelled and observed trends can simply be explained by internal variability. For absolute sea-ice area and sea-ice extent, however, internal variability cannot explain the difference between model and observations for about half the CMIP5 models that we analyse here. All models that we examined have regional biases, as expressed by the root-mean-square error in concentration, that are larger than the differences between individual satellite algorithms.

The Antarctic Sea Ice Response to the Ozone Hole in Climate Models

Abstract It has been suggested that the increase of Southern Hemisphere sea ice extent since the 1970s can be explained by ozone depletion in the Southern Hemisphere stratosphere. In a previous study, the authors have shown that in a coupled atmosphere–ocean–sea ice model the ozone hole does not lead to an increase but to a decrease in sea ice extent. Here, the robustness of this result is established through the analysis of models from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). Comparison of the mean sea ice trends in CMIP3 models with and without time-varying stratospheric ozone suggests that ozone depletion is associated with decreased sea ice extent, and ozone recovery acts to mitigate the future sea ice decrease associated with increasing greenhouse gases. All available historical simulations with CMIP5 models that were designed to isolate the effect of time-varying ozone concentrations show decreased sea ice extent in response to historical ozone trends. In most models, the historical sea ice extent trends are mainly driven by historical greenhouse gas forcing, with ozone forcing playing a secondary role.

Internal Variability in Projections of Twenty-First-Century Arctic Sea Ice Loss: Role of the Large-Scale Atmospheric Circulation

Abstract Internal variability in twenty-first-century summer Arctic sea ice loss and its relationship to the large-scale atmospheric circulation is investigated in a 39-member Community Climate System Model, version 3 (CCSM3) ensemble for the period 2000–61. Each member is subject to an identical greenhouse gas emissions scenario and differs only in the atmospheric model component's initial condition. September Arctic sea ice extent trends during 2020–59 range from −2.0 × 106 to −5.7 × 106 km2 across the 39 ensemble members, indicating a substantial role for internal variability in future Arctic sea ice loss projections. A similar nearly threefold range (from −7.0 × 103 to −19 × 103 km3) is found for summer sea ice volume trends. Higher rates of summer Arctic sea ice loss in CCSM3 are associated with enhanced transpolar drift and Fram Strait ice export driven by surface wind and sea level pressure patterns. Over the Arctic, the covarying atmospheric circulation patterns resemble the so-called Arctic dipole, with maximum amplitude between April and July. Outside the Arctic, an atmospheric Rossby wave train over the Pacific sector is associated with internal ice loss variability. Interannual covariability patterns between sea ice and atmospheric circulation are similar to those based on trends, suggesting that similar processes govern internal variability over a broad range of time scales. Interannual patterns of CCSM3 ice–atmosphere covariability compare well with those in nature and in the newer CCSM4 version of the model, lending confidence to the results. Atmospheric teleconnection patterns in CCSM3 suggest that the tropical Pacific modulates Arctic sea ice variability via the aforementioned Rossby wave train. Large ensembles with other coupled models are needed to corroborate these CCSM3-based findings.

Assessing trend and variation of Arctic sea-ice extent during 1979–2012 from a latitude perspective of ice edge

Arctic sea-ice extent (in summer) has been shrinking since the 1970s. However, we have little knowledge of the detailed spatial variability of this shrinking. In this study, we examine the (latitudinal) ice extent along each degree of longitude, using the monthly Arctic ice index data sets (1979–2012) from the National Snow and Ice Data Center. Statistical analysis suggests that: (1) for summer months (July–October), there was a 34-year declining trend in sea-ice extent at most regions, except for the Canadian Arctic Archipelago, Greenland and Svalbard, with retreat rates of 0.0562–0.0898 latitude degree/year (or 6.26–10.00 km/year, at a significance level of 0.05); (2) for sea ice not geographically muted by the continental coastline in winter months (January–April), there was a declining trend of 0.0216–0.0559 latitude degree/year (2.40–6.22 km/year, at a significance level of 0.05). Regionally, the most evident sea-ice decline occurred in the Chukchi Sea from August to October, Baffin Bay and Greenland Sea from January to May, Barents Sea in most months, Kara Sea from July to August and Laptev Sea and eastern Siberian Sea in August and September. Trend analysis also indicates that: (1) the decline in summer ice extent became significant (at a 0.05 significance level) since 1999 and (2) winter ice extent showed a clear changing point (decline) around 2000, becoming statistically significant around 2005. The Pacific–Siberian sector of the Arctic accounted for most of the summer sea-ice decline, while the winter recovery of sea ice in the Atlantic sector tended to decrease. Keywords: NSIDC ice index; Arctic; sea-ice extent; ice-edge latitude. (Published: 11 September 2014) Citation: Polar Research 2014, 33 , 21249, http://dx.doi.org/10.3402/polar.v33.21249

Temporal and spatial evolution of the Antarctic sea ice prior to the September 2012 record maximum extent

[1] On 24 September 2012 the Antarctic sea ice extent (SIE) reached a new annual daily maximum (ADM) for the satellite era of 19.72 × 106 km2. The largest positive SIE anomalies compared to the mean of all ADMs were found over the northern Amundsen Sea, off the coast of Wilkes Land, with smaller positive anomalies off the Dronning Maud Land coast (30°W to 30°E). The SIE at the ADM is significantly correlated with the extents for the previous 80 days, but the ice growth during the winter of 2012 was close to the climatological rate, and 1 month before the ADM, the SIE was near the recent mean. Deep depressions in the circumpolar trough since late August 2012 resulted in strong southerly flow and marked northward sea ice advection. The linear trend in SIE suggests that it contributed ~40% to the 2012 anomaly, with depression activity adding ~60%.